The present invention relates generally to managing and updating cached data, and more particularly, to dynamic incremental updating of online analytical processing (OLAP) data cubes.
Business Intelligence (BI) is a technology-driven process for analyzing and aggregating data from transactional databases, wherein cubes of data are prepared or refreshed at regular intervals (usually nightly). Online analytical processing (OLAP) is the technology behind many BI applications, wherein one or more computer processors perform a multidimensional analysis of data. All data gathered during OLAP are collected into fact tables. Most customer systems that generate huge amount of data cannot be “transactionally” analyzed or evaluated. Accordingly, OLAP data is typically aggregated into OLAP data cubes. OLAP data cubes generated during this process may be exposed as dashboards or reports to product managers or customer segments for them to glean business insights. Examples of data that may be analyzed via OLAP include click stream data from web logs of online portals and search engines, banking transactions, store logistics, point of sale data, etc., which are then exposed as reports to users. Typically, one or more processors execute a batch job to read transactional data, mine data logs, perform calculations, summations, aggregations, etc., and load results into OLAP data cubes on a nightly, weekly, monthly, or yearly basis.